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From Traffic Modeling to Smart Cities and Digital Democracies
Last Updated: 2026-06-03 00:07:38
Abstract
This seminar will present speakers who discuss the challenges and opportunities arising for our cities and societies with the digital revolution.
Objective
To collect credit points, students must actively contribute and give an individual, circa 20-minute presentation in the seminar on a subject agreed upon with the lecturer. After the presentation, it will be discussed and graded.
Content
This seminar will present speakers who discuss the challenges and opportunities arising for our cities and societies with the digital revolution. Besides discussing questions of automation using Big Data, AI and other digital technologies, we will also reflect on the question of how democracy could be digitally upgraded, and how citizen participation could contribute to innovation, sustainability, resilience, and quality of life. This includes questions around collective intelligence and digital platforms that support creativity, engagement, coordination and cooperation.
Resources
Literature
• Banerjee, I., Warnier, M., Brazier, F. M. T., et al. (2020). SOS—Self-organization for survival: Introducing fairness in emergency communication to save lives. • Batty, M., Axhausen, K. W., Giannotti, F., et al. (2012). Smart cities of the future. • Caldarelli, G., Arcaute, E., Barthelemy, M., et al. (2023). The role of complexity for digital twins of cities. • Helbing, D. (2001). Traffic and related self-driven many-particle systems. • Helbing, D. (2009). An analytical theory of traffic flow. • Helbing, D. (2020, June 18). Digital democracy: How to make it work? • Helbing, D., & Argota Sánchez-Vaquerizo, J. (2023). Digital twins: Potentials, ethical issues and limitations. • Helbing, D., & Klauser, S. (2018). How to make democracy work in the digital age. • Helbing, D., & Pournaras, E. (2015). Society: Build digital democracy. • Helbing, D., Mahajan, S., Hänggli Fricker, R., et al. (2023). Democracy by design: Perspectives for digitally assisted, participatory upgrades of society. • Helbing, D., Fanitabasi, F., Giannotti, F., et al. (2021). Ethics of smart cities: Towards value-sensitive design and co-evolving city life. • Korecki, M., Dailisan, D., & Helbing, D. (2023). How well do reinforcement learning approaches cope with disruptions? The case of traffic signal control. • Lorenz, J., Rauhut, H., Schweitzer, F., et al. (2011). How social influence can undermine the wisdom of crowd effect. • Maahsen-Milan, A., Pellegrino, M., Oliva, L., & Simonetti, M. (2013). Urban architecture as connective-collective intelligence: Which spaces of interaction? • Mahajan, S., Hausladen, C. I., Argota Sánchez-Vaquerizo, J., et al. (2022). Participatory resilience: Surviving, recovering and improving together. • Mann, R. P., & Helbing, D. (2017). Optimal incentives for collective intelligence. • Mulgan, G. (2018). Big mind: How collective intelligence can change our world. • Pournaras, E. (2020). Proof of witness presence: Blockchain consensus for augmented democracy in smart cities. • Pournaras, E., Pilgerstorfer, P., & Asikis, T. (2018). Decentralized collective learning for self-managed sharing economies. • Segaran, T. (2007). Programming collective intelligence: Building smart web 2.0 applications. • Tovey, M. (Ed.). (2008). Collective intelligence: Creating a prosperous world at peace. • Treiber, M., & Kesting, A. (2013). Traffic flow dynamics: Data, models and simulation. • Woolley, A. W., Chabris, C. F., Pentland, A., et al. (2010). Evidence for a collective intelligence factor in the performance of human groups. • Yang, S., Xu, J.-X., Li, X., et al. (2017). Iterative learning control for multi-agent systems coordination.
General Information
- Language
- English
- Levels
- DS , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 40
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar | From Traffic Modeling to Smart Cities and Digital Democracies | No time listed | 2 h weekly |
Offered In
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Science in Perspective (In “Science in Perspective”-courses students learn to reflect on ETH’s STEM subjects from the perspective of humanities, political and social sciences. Only the courses listed below will be recognized as "Science in Perspective" courses.)
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Type A: Enhancement of Reflection Competence (SiP courses are recommended for bachelor students after their first-year examination and for all master- or doctoral students. All SiP courses are listed in Type A. Courses listed under Type B are only recommendations for enrollment for specific departments.)
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Type B: Reflection About Subject-Specific Methods and Contents (Subject-specific courses. Particularly relevant for students interested in those subjects. All these courses are also listed under the category “Typ A”, and every student can enroll in these courses.)
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Doctorate Humanities, Social and Political Sciences (More Information at: )
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